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AI Product Manager - BFS

Hyderabad, Remote, Bangalore, Chennai
Job Description
Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer full-stack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow.

Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore, and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. Many of our team leaders rank in the Top 10 and 40 Under 40 lists, exemplifying our dedication to innovation and excellence.

We are a Great Place to Work-Certified™ (2022-24), recognized by analyst firms such as Forrester, Gartner, HFS, Everest, ISG and others. We have been ranked among the ‘Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial Times, Economic Times and Analytics India Magazine.

About the role:
We at Tiger Analytics are looking for AI Product Managers in the Banking & Financial
Services space. This is a new and evolving role, and while the job description (JD)
below serves as a guideline, the role will evolve and grow with time, similar to the AI
space itself.
Candidates may come from an Analytics, Data Science, or AI consulting background, or
may have extensive experience in the functional aspects of banking (commercial, retail,
fraud, credit, etc.) with recent exposure to and learning in the AI space. Any sort of
hands-on Analytics and Data Science experience in past or present roles is preferred.

Banking - AI product managers
The AI Product Manager is a critical role responsible for driving the strategy,
development, launch and delivery of Artificial Intelligence and Machine Learning (AI/ML)
powered products specifically for the banking and financial services domain. This role
acts as the key interface between client needs, industry expertise, and technology
delivery, ensuring our AI solutions deliver measurable business value and adhere to
strict regulatory standards. Along with the skillsets and experience mentioned below, we
are looking for people who are flexible and willing to scale and adapt in this evolving
field. This will necessitate having above average communication and stakeholder
management skills and flexibility to adapt and learn/scale in the area of AI product
Management in Banking and Financial services.

Description of Work
The core mission is to identify and solve high-value problems for banking clients using
AI. This involves managing the entire product lifecycle from ideation and client-specific
customization through to deployment and delivery handoff.
Key Responsibilities Include:
● Customization and Solutioning: Customize existing organizational AI product
assets and solutions (e.g., fraud engines, NLP-based chat solutions) for specific
banking client use cases, accounting for their unique data structures and
regulatory environments.
● Domain Expertise & Innovation: Brainstorm and conceptualize new Banking-
specific AI capabilities and solutions by leveraging your expertise as a Banking
product/domain Subject Matter Expert (SME), translating emerging trends into
concrete product opportunities (e.g., new generative AI applications for
compliance).

● Product Definition & Prototyping: Define the product vision and features,
translating client requirements into clear, measurable user stories. Lead the
process of MVP (Minimum Viable Product) and Wireframe development to
visually communicate proposed solutions to both internal teams and external
clients.
● Execution & Delivery: Own the end-to-end product lifecycle in a client delivery
context. Drive Banking AI capability delivery for both new and existing clients,
coordinating with Data Science, Engineering, and Implementation teams to
ensure timely and high-quality deployment.
● Technical Showcase & Enablement: Jointly work with the Technology team to
build and refine AI Demos and Showcases specific to Banking and Financial
Services to support sales efforts, thought leadership, and client engagement.

Primary Skillsets
Category Skills & Expertise
Product
Management
Core

Product Strategy & Road mapping, GTM & Pricing, MVP
definition, Agile/Scrum, Stakeholder Management, and strong
analytical skills for defining and tracking KPIs.

Financial
Services Domain

In-depth knowledge of banking value chains (e.g., Retail,
Commercial, Investment Banking) and core financial processes
(e.g., Fraud/Risk Management, Regulatory Compliance,
Trading).

AI/ML Acumen &
Prototyping

Understanding of the AI/ML lifecycle and core concepts
including LLMs, RAG, Agentic AI. Ability to quickly develop
product mockups and wireframes to articulate the AI solution.

Consulting &
Client Focus

Proven ability to gather requirements from clients, customize
solutions for a specific customer, and clearly articulate
technical value to a non-technical audience.

Regulation &
Ethics

Deep understanding of regulatory compliance in finance (e.g.,
KYC, AML, GDPR) and principles of Responsible AI (Fairness,
Explainability, Transparency).

Secondary Skillsets
Category Skills & Expertise

Technical Tools

Familiarity with cloud platforms (AWS, Azure, GCP) and their
ML services, and experience with data visualization tools
(e.g., Tableau, Power BI).

Solution
Architecture

Basic understanding of data pipelines, integration methods
(API design), and how AI models are deployed and monitored
in a production banking environment.

Business Case
Development

Experience in quantifying the ROI of AI projects and creating
compelling business cases to gain client and executive buy-in.
Pre-Sales Support Experience creating and conducting technical demonstrations

and showcases for potential and existing clients.

Data & Quality
Assurance

Hands-on comfort with defining data requirements for
modeling and working with QA/Testing teams to validate AI
model behavior and output quality.